This research is part of a larger, long-term effort to aid the development of radiological interventions based on in vivo multimodal imaging, mainly quantitative PET imaging, for cancer diagnosis and treatment. These image-guided interventional procedures include biopsy, minimally invasive drug delivery and tumor ablation. Currently, PET imaging using [18F]-fluorodeoxyglucose (FDG) for tumor-detection does not utilize its full clinical potential. Accordingly, our research project addresses the correlation between PET measured tracer transport rate parameters (for FDG in this project) and histopathologically evaluated cancer prognostic factors. These cancer prognostic factors include pathologic type and grade, proliferation rate, p53 expression, etc. They are more useful for patient categorization, more crucial for treatment decisions, and more important for early assessment of the outcome of interventional procedures because they provide cellular level information as well as the microenvironment of the cancer. Our initial objective is to establish the woodchuck model of Hepatocellular Carcinoma (HCC) for quantitative FDG-PET imaging. Through multimodal imaging, we will align images from PET, CT and histology. Using functional analysis, we will correlate FDG transport parameters with cancer prognostic factors. We have assembled a strong research team with the needed expertise to accomplish our goal this BRG project. We hope that such correlation, if established, will lead to more successful cancer prognosis and early prediction of treatment efficacy and will thus have a huge impact on patient management. The methodology developed in this research can be applied to other tracers and used for other problem-specific research.